Feb 17, 2025 · 59m · capital-allocators
Michael Choe - Atomization of Private Equity Decisions at Charlesbank (EP.432)
gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions
In this episode of Capital Allocators, host Ted Seides interviews Michael Choe, CEO of Charlesbank Capital Partners, exploring how the firm transforms private equity investing into a systematic, probabilistic decision-manufacturing process. Choe discusses his unique personal background, the flaws of traditional five-year LBO underwriting, and Charlesbank's proprietary 'Two-Year Fan of Outcomes' Monte Carlo framework for unlocking asymmetric upside and institutional excellence.
How this conversation actually went
Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Ted holds 18.1% of the talking time here. How this is scored →
speaking balance: gold is Ted, purple is the guest (3 minute bins)
Mike vigorously critiques the industry standard 5-year LBO model as fundamentally flawed, arguing it manufactures false precision and masks real outcome dispersion.
Hardest push from Ted ▶ 37:25 Ted pressing on empirical drivers of successTed presses Mike to move beyond the modeling theory and provide concrete empirical proof of what historical factors actually drove Charlesbank's investment performance.
Biggest teaching moment ▶ 30:20 Probabilistic math on customer retention riskMike gives a clear mathematical demonstration showing how deal teams deceive themselves on sticky accounts, proving two 90% probabilities compound to a 1/3 risk of losing a client over two years.
Ted holds their own ▶ 13:40 Ted contextualizing Harvard Management Company's spinoutsTed highlights his deep allocator expertise by contrasting Jack Meyer's in-house investment model at Harvard with David Swensen's third-party manager model at Yale.
the scores for every segment, with the reasoning behind each
| Chapter | Topic | Ted as informed peer | Guest teaching | Guest disagreement | Ted pushing back | Why |
|---|---|---|---|---|---|---|
| Episode Overview and Host Monologue | 1 | 2 | 0 | 0 | Host sets up the episode in monologue before asking about Mike's early childhood background. Mike shares his unexpected move back to Korea and adapting to a different educational system. | |
| Parental Influences, Logic vs. Decisiveness, and Decision Studies | 2 | 3 | 0 | 0 | Ted probes how parental influences shaped Mike's view of decision-making. Mike explains the contrast between his logical but indecisive father and decisive mother. | |
| Career Transition from Science to McKinsey and Charlesbank | 4 | 3 | 0 | 0 | Ted demonstrates solid institutional knowledge regarding Jack Meyer and Harvard Management Company's in-house model versus Yale. Mike elaborates on the spinout history of Charlesbank. | |
| Evolution of Investment Philosophy: Manufacturing Sound Decisions | 3 | 4 | 1 | 0 | Mike explains shifting away from crude valuation heuristics toward viewing the firm as a decision-manufacturing engine where the atomic unit of production is a decision. | |
| Shifting from EBITDA Multiples to Two-Year Probability Distributions | 3 | 4 | 1 | 0 | Mike deconstructs the industry-standard TEV/EBITDA metric, explaining why cash flow yield assumptions fall apart in modern PE exits and introducing the 2-year forward probability distribution. | |
| Flaws of 5-Year LBO Models and the 2-Year Fan of Outcomes | 3 | 5 | 2 | 0 | Mike challenges standard industry practice, pointing out how 5-year LBO models promote severe anchoring bias and uncalibrated base cases compared to actual wide outcome dispersion. | |
| Probabilistic Modeling, Accountability, and Asymmetric Upside KPIs | 3 | 5 | 1 | 0 | Mike educates on replacing base/bull/bear stories with Monte Carlo KPIs, tracking the percentage of simulated paths yielding >30% IRR or capital impairment to target upside asymmetry. | |
| Quantifying Unseen Risks: Recessions and Customer Concentration | 3 | 5 | 1 | 0 | Mike explains how traditional modeling hides compound risk, demonstrating how two independent 10% annual customer churn risks compound to a 33% chance of losing a top account across two years. | |
| Sponsor Message: AI-Native Investment Operations with Ridgeline | 2 | 1 | 0 | 0 | Segment includes a mid-roll advertisement read followed by Ted prompting how downstream modeling shapes upstream origination workflows. | |
| Identifying Asymmetric Opportunities in Specialized Human Capital Services | 2 | 4 | 0 | 0 | Mike details targeting CPA and tax accounting firms due to strong customer retention, capital efficiency, and misunderstood income scrape mechanics. | |
| Empirical Regression Findings on M&A, Management, and Entry Multiples | 3 | 5 | 1 | 0 | Mike shares empirical regression findings that debunk common industry assumptions, noting no correlation between entry multiples and returns, and strong returns from programmatic M&A. | |
| Implementation Obstacles and Portfolio Company Communication | 3 | 4 | 0 | 0 | Mike discusses practical hurdles in probabilistic modeling, including avoiding over-complexity and distinguishing bad luck in tail events from flawed decision logic. | |
| Measuring Model Efficacy via Portfolio Breakout Performance | 3 | 4 | 0 | 0 | Mike outlines tracking breakout returns across recent vintages and applying asymmetric decision framing to internal talent retention and firm expansion. | |
| Evaluating the Evolution and Valuation Dynamics of Private Equity | 3 | 4 | 1 | 0 | Mike analyzes structural shifts in private equity valuations, plateauing entry multiples, and liquidity cushions supported by massive global private capital allocations. | |
| Macro Debt Cycle Risks vs. Excitement for Talent Science | 2 | 3 | 0 | 0 | Discussion moves from macro debt restructuring risks to rapid-fire personal questions including cooking, tutoring in Seoul, and books on near-death experiences. | |
| Building a Systematic, Enduring Investment Institution | 2 | 3 | 0 | 0 | Mike closes by detailing the firm's vision of building an enduring institutional decision system rather than relying on star individuals. |